Within these pages, readers will find information related to the integration and management of crowdsourced data. Crowdsourced data include active data generated through the use of social media apps (e.g., Waze, Twitter), as well as passive data collected via cell phones (e.g., probe speed data, traveler behavior), transponders (e.g., E-ZPass, freight), and vehicle systems (heavy breaking, wiper on/off, CVs). Crowdsourced data have tremendous potential to offer new insights; however, the volume and speed at which these data are generated are unprecedented. To handle these “big data,” modern, flexible, and scalable methods to manage these data must be adopted by transportation agencies if the data will be used to facilitate better decision-making.
Currently, the most common applications of crowdsourced data are traveler information and incident management; however, agencies are expanding use in areas such as traffic signal timing, maintenance, road weather, and work zone management. The major barriers for agencies seeking to more effectively use crowdsourced data include understanding and assessing the quality of the data, storing and managing the large amount of data, and turning the data into information to support operational decision-making. In some cases, agencies struggle to make the business case for purchasing or using the data because management does not fully understand the potential benefits of the data.
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Vehicle probe data includes information from mobile cellular devices, fleet vehicles with embedded global positioning systems (GPS) devices, connected vehicle telematics, and mobile applications (cell phone, tablet, or other devices) that track user locations. These data, typically provided by third-party vendors who capture, manage, analyze, and anonymize the data, provide cost-effective information across the transportation system. As such, transportation agencies are increasing adopting the use of vehicle probe data to support the planning and operation of transportation systems. This document serves as a primer on vehicle probe data, including the sources and applications for probe data, the challenges agencies need to address to effectively use the data, and the current and future opportunities for using vehicle probe data.
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Crowdsourcing turns transportation system users into real-time sensors on system performance, providing low-cost, high-quality data on traffic operations, roadway conditions, travel patterns, and more. When combined with traditional data, crowdsourcing helps agencies implement proactive strategies that improve incident detection, traffic signal retiming, road weather management, traveler information, and other operational programs.
FHWA’s Every Day Counts Round 5 (EDC-5), and now EDC-6, Crowdsourcing for Operations innovation is the best source of information on the current state of practice in the use of crowdsourced data by transportation agencies.
This guidebook for state DOTs contains over 100 recommendations for managing data from emerging technologies, such as crowdsourcing, in a modern way. It also contains a roadmap for implementing the guidance, as well as several tools including a modern data management capability maturity self-assessment. This guidebook is a good resource for agencies grappling with how to manage new, large datasets, including crowdsource data.
